Krishna Sai Vootla, Developer in Bengaluru, Karnataka, India
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Krishna Sai Vootla

Verified Expert  in Engineering

Machine Learning Developer

Bengaluru, Karnataka, India

Toptal member since October 31, 2019

Expertise
Machine LearningArtificial IntelligenceCode ReviewNLPLLMRAGGitPythonSQLJiraPyTorchCloud EngineeringAlgorithmsRStudio Shiny
Bio

Krishna is a machine learning engineer who is curious and passionate about applied deep learning in computer vision, NLP, and reinforcement learning. He has four years of experience with machine learning, including being a part of the analytics division of JP Morgan Chase & Co. Krishna is a great communicator and enthusiastic developer.

Portfolio

The Weather Company
AI Agents, Large Language Models (LLMs), FastAPI, Terminal...
Organifi
Python 3, Natural Language Processing (NLP)...
Multithread
Python 3, Flask, Neo4j, OpenAI GPT-4 API, Google Cloud Platform (GCP), Docker...

Experience

  • Machine Learning - 7 years
  • Python - 6 years
  • Natural Language Processing (NLP) - 4 years
  • Deep Learning - 3 years
  • LangChain - 2 years
  • AI Chatbots - 2 years
  • Large Language Models (LLMs) - 2 years
  • OpenAI - 1 year

Availability

Full-time

Preferred Environment

PyCharm, Tableau, RStudio, Spyder, Jupyter Notebook, SQL, Machine Learning, Python

The most amazing...

...achievement of mine is winning 3rd prize globally in the Intel ESDC competition held in Shanghai, China.

Work Experience

Senior Data Scientist | AI Engineer

2024 - PRESENT
The Weather Company
  • Developed pipelines to create embeddings for relational data using graph neural networks.
  • Built an end-to-end model explainability pipeline to summarize SHAP and PDP analytics.
  • Implemented and deployed end-to-end machine learning models using cutting-edge techniques like self-supervised learning.
Technologies: AI Agents, Large Language Models (LLMs), FastAPI, Terminal, Bayesian Inference & Modeling, TensorFlow, Bash Script, Git, LangChain, AI Design, Document Parsing, AI Programming, Recommendation Systems, PyTorch, Fine-tuning, FAISS, Pinecone, Modeling, Statistics, Applied Statistics, Statistical Methods

Data Scientist | AI Engineer

2020 - 2024
Organifi
  • Developed and deployed an NLP pipeline to extract and summarize opinions and feedback from customer product reviews.
  • Built data pipelines in AWS and GCP for a reporting and analytics data warehouse.
  • Built numerous executive summary dashboards in Tableau by identifying key metrics to track goals specific to individual teams.
  • Forecasted time series eCommerce demand for inventory and supply chain optimization using SARIMAX.
Technologies: Python 3, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Sentiment Analysis, Data Analytics, BigQuery, Google Cloud Functions, Google Cloud, Tableau, Tableau Desktop Pro, MySQL, Amazon Web Services (AWS), AWS Lambda, Amazon RDS, Data Science, Technical Hiring, Code Review, Interviewing, Source Code Review, SQL, Machine Learning, Python, Deep Learning, Dplyr, AWS Glue, Data Modeling, Snowflake, Databases, Artificial Intelligence (AI), Jupyter, Scikit-learn, Anaconda, Team Leadership, Google Cloud Platform (GCP), Agile, Jira, Clustering, Clustering Algorithms, DBSCAN, Hierarchical Clustering, K-means Clustering, Terminal, Bayesian Inference & Modeling, TensorFlow, Bash Script, Git, AI Design, Document Parsing, AI Programming, Fivetran, Microsoft Power BI, Data Build Tool (dbt), PyTorch, Data Engineering, FAISS, Pinecone, Modeling, Statistics, Applied Statistics, Forecasting, Statistical Methods

Back-end Data Engineer

2023 - 2023
Multithread
  • Developed an end-to-end ETL pipeline from scratch to load data into a graph database and relational database.
  • Built back-end APIs to create customized email text for reaching out to leads using OpenAI API.
  • Created back-end APIs to manipulate and manage data in the graph database.
Technologies: Python 3, Flask, Neo4j, OpenAI GPT-4 API, Google Cloud Platform (GCP), Docker, Vector Search, Clustering, Clustering Algorithms, DBSCAN, Hierarchical Clustering, K-means Clustering, FastAPI, Terminal, Bayesian Inference & Modeling, TensorFlow, Bash Script, Git, Document Parsing, Back-end Development, Data Engineering, Pinecone, Asynchronous Programming

Analyst

2019 - 2019
JP Morgan Chase & Co
  • Designed and built a next-generation merchant acquisition tool in R Shiny for a credit card business.
  • Provided pricing analysis of credit card business.
  • Built and integrated a minimum revenue model based on customer demographics.
Technologies: Tableau, Python, R, Code Review, Source Code Review, SQL, Machine Learning, Jupyter, Scikit-learn, Artificial Intelligence (AI), Algorithms, Terminal, Bayesian Inference & Modeling, Git, Data Build Tool (dbt), Statistics, Statistical Methods

Business Analyst

2018 - 2019
Tredence Analytics
  • Segmented retail customers based on their shopping behavior by using random forest.
  • Designed, built, and deployed an end-to-end machine learning pipeline.
  • Performed marketing analysis of a leading retail company in the US.
Technologies: Tableau, R, Python, Interviewing, Source Code Review, Task Analysis, Data Science, SQL, Machine Learning, Jupyter, Anaconda, Artificial Intelligence (AI), Terminal, Git, Data Build Tool (dbt), PyTorch, Modeling, Statistics

Software Analyst

2017 - 2018
Capgemini
  • Scraped the web for collecting unstructured data present on a website.
  • Created and deployed various executive summary dashboards.
  • Automated data cleaning pipelines to save significant person-hours every week.
Technologies: Python, MySQL, Linux, Task Analysis, Git

Experience

LLM Chatbot for Interacting with Documents

This advanced streamline-based application leverages cutting-edge generative AI technology to provide an immersive, interactive chat experience with PDF documents. Users can upload their PDFs, and the application intelligently analyzes the content, enabling various interactive features that make the information more accessible and engaging.

Users can use this application to achieve the following:
1. AI-powered summarization
2. Interactive Q&A

GitHub Link: https://github.com/krishnasaivootla/ChatWithDocs/blob/main/streamlit_app.py

AnalyticsGPT: LLM-based Data Analysis

AnalyticsGPT is a cutting-edge data analysis tool powered by a state-of-the-art language learning model (LLM), where I designed it to transform the way businesses, researchers, and data enthusiasts interact with their datasets, AnalyticsGPT leverages the advanced capabilities of generative AI to provide deep insights, automate data interpretation, and facilitate an intuitive analysis experience.

At the core of AnalyticsGPT is its LLM, which understands and processes complex data patterns and trends. Users can interact with their data through natural language queries, making data analysis more accessible and less time-consuming. Whether you're looking to identify key trends, predict future patterns, or simply explore your data, AnalyticsGPT offers a user-friendly platform that caters to both seasoned analysts and those new to data science.

GitHub Link: https://github.com/krishnasaivootla/AnalyticsGPT/tree/main

Multi-modal Fully Convolutional Network for Semantic Segmentation

https://github.com/prml615/prml
A fully convolutional network (FCN-32s) trained to semantically segment forest scene images with RGB and nir_color input images.

The project was developed to help unmanned drones in smooth navigation. The model is trained and tested on still images of forest scenes.

I used Intel Edison and Microsoft Kinect for proof of concept and prototype creation.

Smart Medical Network

I worked on a smart medical network for Intel ESDC 2016, Shanghai. The project aimed to create an ecosystem of a medical network that stores the clinical and real-time data of patients for smoother and quicker diagnosis in an emergency.

AI Puppy Influencer

I built an automated short video content creation pipeline that uses AI agents to generate content ideas, build scripts for the reels, and generate images from text and videos from images in ComfyUI hosted in Google Colab using Stable Diffusion and AnimateDiff.

Education

2013 - 2017

Bachelor of Technology Degree in Electrical Engineering

Indian Institute of Technology Gandhinagar - Gandhinagar, India

Certifications

MARCH 2020 - PRESENT

Statistical Learning

Stanford Online

OCTOBER 2019 - PRESENT

Sentiment Analysis in Python

DataCamp

MARCH 2019 - PRESENT

Building Web Applications in R with Shiny: Case Studies

DataCamp

MARCH 2019 - PRESENT

Building Web Applications in R with Shiny

DataCamp

OCTOBER 2018 - PRESENT

CodeChef Certified Data Structure & Algorithms Programme

CodeChef

SEPTEMBER 2018 - PRESENT

Intermediate R

DataCamp

AUGUST 2018 - PRESENT

Data Manipulation in R with dplyr

DataCamp

JULY 2018 - PRESENT

Introduction to R

DataCamp

MARCH 2018 - PRESENT

Python A-Z: Python for Data Science with Real Exercises!

Udemy

MARCH 2018 - PRESENT

SQL - MySQL for Data Analytics & Business Intelligence

Udemy

FEBRUARY 2018 - PRESENT

Structuring Machine Learning Projects

Coursera

Skills

Libraries/APIs

PyTorch, Keras, NumPy, Pandas, Matplotlib, Ggplot2, Scikit-learn, TensorFlow, Tidyverse, Beautiful Soup, Standard Template Library (STL), SciPy, OpenCV

Tools

Jira, Git, Tableau, Dplyr, Scikit-image, Looker, AWS Glue, Terminal, ComfyUI, Microsoft Power BI, PyCharm, Jupyter, Spyder, BigQuery, Tableau Desktop Pro, ChatGPT, Amazon SageMaker

Languages

SQL, Python, Python 3, R, Snowflake, Bash Script, C++, C, Embedded C

Platforms

Google Cloud Platform (GCP), Amazon Web Services (AWS), Docker, RStudio, Linux, Oracle, Arduino, Raspberry Pi, Raspberry Pi 3 GPIO, Jupyter Notebook, Anaconda, AWS Lambda, Azure

Frameworks

RStudio Shiny, Microsoft Kinect, Flask, LlamaIndex

Paradigms

Agile, Asynchronous Programming

Storage

MySQL, Databases, Google Cloud, Google Cloud Storage, Neo4j

Industry Expertise

Applied Statistics

Other

Freelancing, Machine Learning, Natural Language Processing (NLP), Data Science, Artificial Intelligence (AI), Technical Hiring, Code Review, Source Code Review, Large Language Models (LLMs), AI Chatbots, Generative Artificial Intelligence (GenAI), Retrieval-augmented Generation (RAG), FAISS, Pinecone, Modeling, Statistics, Algorithms, Neural Networks, Deep Neural Networks (DNNs), Deep Learning, Computer Vision, Data Analytics, Data Reporting, Exploratory Data Analysis, Statistical Data Analysis, Statistical Learning, Statistical Modeling, Analytics, Predictive Analytics, Statistical Analysis, Data Analysis, Artificial Neural Networks (ANN), Interviewing, Task Analysis, Generative Pre-trained Transformers (GPT), Chatbots, Minimum Viable Product (MVP), APIs, Data Modeling, LangChain, OpenAI GPT-4 API, Open-source LLMs, Team Leadership, Llama 3, Mistral AI, Prompt Engineering, Multi-agent Systems, Vector Search, AI Agents, Clustering, Clustering Algorithms, DBSCAN, Hierarchical Clustering, K-means Clustering, FastAPI, Bayesian Inference & Modeling, AI Design, Document Parsing, AI Programming, Back-end Development, Recommendation Systems, Fivetran, Data Build Tool (dbt), Data Engineering, Reinforcement Learning, Forecasting, Statistical Methods, Quantitative Analysis, Sentiment Analysis, Google Cloud Functions, Amazon RDS, Scalable Vector Databases, Chatbot Conversation Design, OpenAI, Stable Diffusion, Image to Video, Text to Video, AI Content Creation, Kling AI, Text to Image AI, Image to Text, Text to Image, Fine-tuning

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